September 22, 2017
Connecticut, for example. Last year’s state budget (the current state budget is still being hammered out) projected $731 million to cover health care costs for retired state employees in 2017, compared to just $698 million for the health care costs of current employees.
Because Connecticut failed to save-up for the long-term costs of their retirees, state taxpayers are now paying more money to cover the costs of people who aren’t providing any government services—because they are retired—than for people who actually are.
Source: The Hidden $700 Billion Debt Owed to Public Workers – Hit & Run : Reason.com
February 12, 2017
We compare healthcare spending in public and private Medicare using newly available claims data from Medicare Advantage (MA) insurers. MA insurer revenues are 30 percent higher than their healthcare spending. Healthcare spending is 25 percent lower for MA enrollees than for enrollees in traditional Medicare (TM) in the same county with the same risk score. Spending differences between MA and TM are similar across sub-populations of enrollees and sub-categories of care, with similar reductions for “high value” and “low value” care. Spending differences primarily reflect differences in healthcare utilization; spending per encounter and hospital payments per admission are very similar in MA and TM. Geographic variation in MA spending is about 20 percent higher than in TM, but geographic variation in hospital prices is about 20 percent lower. We present evidence consistent with MA plans encouraging substitution to less expensive care, such as primary rather than specialist care, and outpatient rather than inpatient surgery, and with employing various types of utilization management. Some of the overall spending differences between MA and TM may be driven by selection on unobservables, and we report a range of estimates of this selection effect using mortality outcomes to proxy for selection.
Source: Healthcare Spending and Utilization in Public and Private Medicare by Vilsa Curto, Liran Einav, Amy Finkelstein, Jonathan Levin, Jay Bhattacharya :: SSRN
February 12, 2017
We examine in how far people’s experiences of income inequality affect their preferences for redistribution. We use several large nationally representative datasets to provide evidence that people who have experienced more inequality while growing up are less in favor of redistribution, after controlling for income, demographics, unemployment experiences and current macro-economic conditions. They are also less likely to consider the prevailing distribution of incomes to be unfair, suggesting that inequality experiences affect the reference point about what is a fair division of overall income. Finally, we conduct an experiment to show that individuals randomly exposed to environments promoting inequality in the experience stage of the experiment redistribute less in a subsequent behavioral measure.
Source: Experienced Inequality and Preferences for Redistribution by Christopher Roth, Johannes Wohlfart :: SSRN
February 10, 2017
We use a novel retail panel with more than six years of detailed transaction records to study the effect of participation in the Supplemental Nutrition Assistance Program (SNAP) on household spending. We frame our approach using novel administrative data from the state of Rhode Island. The marginal propensity to consume SNAP-eligible food (MPCF) out of SNAP benefits is 0.5 to 0.6. The MPCF out of cash is much smaller. These patterns obtain even for households for whom SNAP benefits are economically equivalent to cash in the sense that benefits do not cover all food spending. We reject the hypothesis that households respect the fungibility of money in a semiparametric setup. A post-hoc model of mental accounting rationalizes these facts and others.
Source: How are Snap Benefits Spent? Evidence from a Retail Panel by Justine S. Hastings, Jesse M. Shapiro :: SSRN
February 9, 2017
As President Donald Trump begins his term, he faces perhaps the most daunting fiscal situation of any incoming president. President Trump enters office with high levels of debt, rising deficits, major trust funds facing shortfalls, and no agreement on how to address these challenges.
Source: President Trump’s Historic Debt Dilemma | Committee for a Responsible Federal Budget
February 7, 2017
Fragmented health care occurs when care is spread out across a large number of poorly coordinated providers. We analyze care fragmentation, an important source of inefficiency in the US healthcare system, by combining an economic model of regional practice styles with an empirical study of Medicare enrollees who move across regions. Roughly sixty percent of cross-regional variation in care fragmentation is independent of patients’ clinical needs or preferences for care. A one standard deviation increase in regional fragmentation is associated with a 10% increase in utilization. Our analysis also identifies conditions under which anti-fragmentation policies can improve efficiency.
Source: Causes and Consequences of Fragmented Care Delivery: Theory, Evidence, and Public Policy by Leila Agha, Brigham R. Frandsen, James B. Rebitzer :: SSRN
February 7, 2017
In this period of high uncertainty about future economic growth, we have developed a growth projection tool for 13 advanced countries and the euro area at the 2100 horizon. This high uncertainty is reflected in the debate on the possibility of a ‘secular stagnation’, fuelled by the short-lived Information and Communication Technology (ICT) shock and the current low productivity and GDP growth in advanced countries. Our projection tool allows for the modelling of technology shocks, for different speeds of regulation and education convergence, with endogenous capital growth and TFP convergence processes. We illustrate the benefits of this tool through four growth scenarios, crossing the cases of a new technology shock or secular stagnation with those of regulation and education convergence or of absence of reforms. Over the 2015-2100 period, the secular stagnation scenario assumes yearly TFP growth of 0.6% in the US, leading to a 1.5% GDP growth trend. The technology shock scenario assumes that the third technological revolution will, in the US, provide similar TFP gains to electricity during the second industrial revolution, leading to a 1.4% TFP trend, to which we add a TFP growth wave peaking in 2040, and thus to an average GDP growth rate of 3% in the US. In non-US countries, GDP growth will depend on the implementation of regulation reforms, the increase in education and on the distance to the country-specific convergence target, namely the US, as well. Over the period 2015-2060, for the euro area, Japan and the United Kingdom, benefits from regulation and education convergence would amount to a 0.1 to 0.4 pp yearly growth rate depending on the initial degree both of rigidity and the TFP distance to the US.
Source: Long-Term Growth and Productivity Projections in Advanced Countries by Gilbert Cette, Remy Lecat, Carole Ly-Marin :: SSRN